Deep Dive 12/11/2024 - Dry November but changes are coming - Met Office weekly weather forecast UK

[@metoffice]

Here's a link to that ensembles video kzbin.info/www/bejne/j4OVoYOJp9d9mqM And here's where you can catch up on last Friday's live kzbin.info/www/bejne/gJ-aiYGeh6uEo80

[@chrisa9043]

Loved your deep dive met office.

[@ChristopherMcGrath-p1f]

153 reiga cycles kicks in this week,seismicity volcanism will peak..

[@The-Sea-Dragon-1977]

I'm a Captain in the Merchant Navy, I have studied Met, I'd just like to say that Alex is my favourite Wx forecaster. Informative and I leanr something every time, yet still fun to watch and accessible to the layman, that's a rare talent.

[@HazelKitching]

Agree.ALEX is a brilliant weather forecaster.

[@ChrisJonty]

What a fantastic video. I could listen to Ken talk for hours - his enthusiasm and knowledge came across so clearly. Thanks!

[@Mat1234A]

Thank you as always for the deep dive Alex and to everyone at the Met Office team, you truly don't get this level of commitment anywhere else on the internet and truly appreciate the time it takes to make these. You've inspired me to learn more about the weather which has transformed my knowledge and awareness. Loved the ensemble interview that was so fascinating! Thank you!

[@Coolyoghurt22]

I agree. Met Office and the team put so much time for us and I really appreciate everything they do. 👍

[@suewright1299]

Very many thanks for a really brilliant Deep Dive Alex and Ken! I was absolutely glued to all that Ken was saying and how he described the ensembles! It’ll be a pleasure to have him back at any time. You yourself did a video about ensembles not so long ago Alex and that itself was so very informative, but Ken’s was brilliant, amazing!! 😮 Such an excellent video, I always save the DD’s and anything informative, and this was among the best. Thanks again Alex, Ken and to all the Met Off. Take great care everyone

[@newparknewpark]

Great stuff. I'm a maths teacher and will be showing and discussing some of this in my A level maths lessons

[@ianhodgson9779]

An excellent deep dive. It's great to get insights from the specialists who are usually beavering away behind the scenes

[@T1000-s6l]

Fantastic video. Ken is a delight. It's really inspiring to see someone who you can tell just loves what they do and it seems to be his life. I wonder how many lives have been saved by his enthusiasm. Awesome.

[@RoyPeters-hj3ou]

Absolutely fantastic, this is the kind of forecasting and background information we've been wanting for years. Thank you

[@MissFreyja]

I really enjoyed that deep dive, thank you to both of you for presenting it and I didn't get confused which is amazing because my maths is awful! This would be a great monthly feature I think.

[@JohnHovenden]

A great deep dive on 12/11/24. Thanks so much to Alex and Ken; a very professional presentation. So glad the Metoffice is producing these discussions on how the weather forecasts are produced, uncertaities etc.. Looking forward to the MetOffice providing more information on their App in the future on the confidence of the forecasts (temp, feels like, rain/wind/etc. ), which I know they have made great strides on recently.

[@tomking5855]

Alex, a thousand thank’s to you and your team at the UK Met Office. I live in Ireland and log on to see your daily and your brilliant deep-dive weather analysis. Keep up the good work and please extend my appreciation to your very competent and entertaining colleagues. Who said weather forecasting was dull!!!’

[@trick700]

Ken! What a man!! Thanks to you both for a fascinating presentation

[@chris__maltby]

Very interesting deep dive, the ensemble part was excellent, thank you

[@LyndaHolloway-c2x]

Thank you, Alex, fabulous as always. Just want to say how good it is to be able to listen to really intelligent conversation and explanation. Keep up the amazing content.

[@wildlifegardener-tracey6206]

That was great watching. Such a brilliant presentation. I've learnt such a lot and have a better understanding of ensembles. So interesting. Thanks all at the met office.

[@jimmagwojo2718]

really fascinating deep dive - more please its great to counter point this with the forecast to help fully apreciate the forecast holistically

[@elaineambrose7413]

Thanks Alex this really was a deeper dive into the way forecasts are prepared . Ken has been so dedicated to ensuring we see the changes in our weather . It will be a game changer for future weathers when we see it in the future ❤ I think there are probably many out there that don’t watch this on KZbin that don’t appreciate the hard work that goes on behind the scenes !! . Once again thanks for all the explanation , quite an eye opener ❤❤❤

[@martywig8653]

We really enjoyed that one thanks. I wish I`d had teachers like you at school!!

[@lion73266]

Alex is a Met Office Legend .

[@strangelyinteresting]

This longer format weather stuff is first class information. Keep up the good work. 👍

[@paulmorris3022]

Hi Alex, this was absolutely brilliant and makes us look at weather in a whole different way and how the Met Office comes up with a pretty accurate weather scenario and confidence. Loving the Deep Dive and the remainder of the new things the whole team are producing. well done

[@Coolyoghurt22]

Thank you Alex and the rest of the Met Office team for putting your time into making these incredible deep dives. Hope you get 300k subs on youtube soon. Take care :)

[@tomasmatulaitis9284]

1 hour video! Yes, please! Fascinating stuff, well done Alex and Ken! Stupid question: it would be interesting if you had a look at your channel stats and lookup for the average numbers on how long people watch these videos. Somehow I sense that no-one is fast forwarding as we all are metheads here! :)

[@briansnell9179]

As a private pilot the weather has a big influence on whether or not I fly on a particular day. Therefore, I am very focussed on how the weather is developing as a flying day approaches. I have a mathematics background, so this video has really enhanced my understanding on how the met office run their models to create a forecast. Great video, thank you.

[@dpeastman]

Fascinating. I love the details of how the modeling actually works.

[@mickeyfilmer5551]

That was a brilliant explanation of how the ensembles are produced. I didn't realise that you varied the starting parameters- but having watched the video- it all makes perfect sense. That must one heck of a supercomputer to do all those calculations. thanks Alex and your team - yet again I have learned something new.

[@richardwalker_]

Verification of the forecast using later actual data is the analysis I’ve been waiting for. Really interesting stuff.

[@KenMylne-f5z]

We use a wide range of verification statistics all the time to monitor our forecasts and, most important, test upgrades to the system. Many are quite mathematical and require a lot of data to get meaningful results. What I showed here was a new method developed by colleagues here in the Met Office a few years ago.

[@DanBlackaz]

Hi Alex - great deep dive and shows the incredibly talented people who work at the met office. One suggestion for a possible future video - you refer to “our super computer” - would be interesting to do a deep dive on what it looks like, how much processing power it has, memory etc for the tech nerds out there like me! Keep up the good work and thanks again!

[@tonetoobtwo]

Thanks Alex, very informative content as always. I've never seen such glee at a rapid drop in air temperature... probably because you're down in Exeter 😂 And thanks to Ken, that was a fascinating insight into the intricacies of modelling. If I'm honest, I was out of my depth once you said 'Well...', but it is always nice to see behind the curtain!

[@paulmarkman5247]

Superb Deep Dive - with an emphasis on the ‘deep’. More of this please - the longer the Deep Dive, the better, in my opinion 😉. Thanks again.

[@mollypenwhistle7918]

Great program, very happy to have long video with more detail explanations of aspects of forecasting and weather development. Really enjoyed this Thank you 😉

[@TheTibmeister]

Wonderful exhibit from you as always. Thanks Alex and Ken ❤

[@michaelrowlandmorris]

Really fantastic bit of this week's Deep Dive on ensembles. Just terrific to be given this kind of chance to understand things. Thank you all

[@johnadams6771]

A real treat to be enlightened as to how the ensemble forecasts work and the reasoning behind them. It would also be interesting to see how the Met Office analyses the observation data for accuracy in the first place, especially with regards to any observations which may look spurious but could be an early indication of the development of something of significance, for example, as in the development of tornados.

[@KenMylne-f5z]

Thanks. We do a lot of quality control of the observations. You are quite right about observations which could be important. If a new storm is developing rapidly, or in a slightly different place than expected, there is a danger that the quality control rejects a crucial observation which should be alerting us to it…so care has to be taken in both automatic and manual checks.

[@imstillme3106]

Excellent communicators talking about fascinating stuff. Can't fault it!

[@darraghgregory1269]

An hour wow 😮😮😮😮, love this 😀 keep it up ,love from Ireland 🇮🇪

[@kevan1831]

Interesting deep dive. Great to watch a presenter who clearly loves his job.

[@geoffcampbell7846]

Super episode, with a great explanation of the ensembles. Much appreciated. 👋

[@jaynedavis4667]

Dear Met Office, please make it snow in Wiltshire, I've got a kitten who loves the outdoors and cant wait to see his reaction to snow! love from Kitten Arnold.

[@KenMylne-f5z]

I love snow too, but I am glad to say that actually making it is beyond our powers!

[@eleanorkidd5840]

Really enjoyed this video with Ken

[@ruperthiggins7358]

Brilliant ‘bonus’! It is so good to get some inside detail of forecasting. Thank you!

[@anthonycline9007]

Love all the new charts and graphs.

[@dorsetblue12]

Another great episode full of information with a really good explanation of ensembles.

[@rosemaryjanemagic]

Thank you. Look forward to this every week. Excellent as ever and it is nice to be treated as intelligent.

[@muddyfox50]

I'd been planning to skip part two but Ken is fascinating.

[@roomiller]

Deep dives can never been too long!

[@nicolepeters6660]

Excellent and entertaining presentation as always ❤

[@dianeanderson6695]

Thankyou Alex for your very interesting Deep Dive.Thankyou❤

[@ClareMarriott-im6sk]

I really enjoyed that, thanks guys ☺️

[@Claymore5]

This was fabulous and so informative! Well done!

[@RedentSC]

love the deep dive

[@MrPhillipgraham]

Cold and sunny 😎. Mild and overcast ☹️. Great DD as usual thanks butty.

[@jeffclarke3191]

excellent prentation, Thank you to all concerned.

[@CliveCarter-wj5ct]

Fantastic video! Loads of information. Brilliant deep dive

[@anthonycline9007]

Like the new 'difference' chart! ( Model comparison)

[@paulgul1]

Excellent and very informative programme, keep them coming, hope to see more like this in the future

[@jasonsjourneys8321]

I loved this hour long treat, thanks so much Alex

[@Mersty.]

Great deep dive as always guys.

[@martryan2060]

Well the field fayres and redwings and some extremely large thrushes Have descended into Ireland in very high numbers So I presume we're in for a bit of chill .

[@stevedean7069]

Brilliant, learn something every time, thanks.

[@pe109]

Not going to be long at this rate until I need a spare day to watch these... as much as I thoroughly enjoy the content, they are getting very long!

[@KenMylne-f5z]

Sorry, enthusiastic scientist getting carried away! Glad you enjoyed it.

[@eddyj.2499]

An excellent and informative presentation thanks.

[@spencersmith7266]

Many thanks, Alex.

[@judithmorris2630]

Cracking stuff! Thank you. Bring us more like this!

[@griffwise1606]

quality info as always!

[@Neelie799]

A very interesting Deep Dive. Thank you.

[@johnmalone5693]

Excellent Deep Dive, make it longer please :)

[@chrisa9043]

Thank you Alex for the deep dive.

[@adamcoole]

Great as ever. Thanks for the deep dive.

[@redsamson70]

New map is great very colorful thanks Alex 👍👍🐶

[@sueelphick9060]

Thanks Alex 😊😊😊😊😊 great work😊😊😊😊

[@StuartTiffany]

Great content guys....love the deep dive 👌

[@duaneheveran]

Very informative as always, thanks.😎

[@rayhaddock779]

Fantastic I learned so much

[@ryanlawrence6823]

Thank you Alex Weather Well done

[@anamariacarvalho6738]

Good afternoon Alexis

[@andy5786]

Cheers Alex brilliant deep dive videos it's going get colder next week coming down from Artic 😊

[@DebbieinNWiltshire]

Fascinating!!! I’ve learnt so much… although it has prompted some questions. Ken very skilfully explained the ensembles the Met Office use to produce a forecast BUT…. Even using all those runs and applying probability modelling there can still be big differences from other forecasts…. By way of example In your deep dive dives you often reference differences between (say) the Met Office model and the European or U.S models.. I even see that there differences for the UK when I look between the Met Office and the BBC. I’m curious what drives these differences in modelling outputs? And what makes them valuable comparators (or Not)

[@KenMylne-f5z]

You are quite right, there are differences between the models run by different forecast centres which sometimes differ more than the ensemble. All models have biases and some of the difference is different biases, but also some perform better in different situations. Ideally the ensemble would spread more and span the types of differences we get between models…the ensemble is not perfect and we are continuing to try to improve it, but for now our forecasters will continue to look at other models from around the world as well. Meteorology is a very collaborative science!

[@trick700]

When my wife asks me if I’m gardening tomorrow, now I can confidently say there’s a 50% probability! 😂

[@Pixieworksstudio]

that was really good, thanks both!

[@HazelKitching]

Thankyou Alex.I hope this cold snap doesn't last too long and that we here on the east coast do not get snow..It fouls up the countries infrastructure.

[@WASYMIQ]

Thank you!

[@Callumsweatherupdates]

Thanks Alex.

[@RubyBaker-b4x]

Very interesting thank you both

[@paolomh113]

It will be good to hear about frost more often.

[@sinwong6612]

Enjoyed this deep drive very much. It would be interesting to see which of various models were closest to the actual outcome.

[@martinoban]

am I right in thinking that if we had had the anticyclonic weather 70 years ago the cities would have had lethal peasoup fog?

[@ricklong7107]

Is Shetland covered by the high res, deterministic or Ensembles models? Looking at the mass it looked like the channel isles were though Shetland was out side the highest res area?

[@greghilton7797]

Please put The Weather Studio on the home page, so we can watch it if we missed it.

[@Ray_M0MXN]

Impressively presented! Very informative

[@DJVOutdoors]

Really good Alex

[@jpjg86]

Thanks for the deep dive, love them. I was wondering if you could cover what happens with the polar jet stream, what it fires, how it would affect us and what would happen if it breaks down?

[@UCCLdIk6R5ECGtaGm7oqO-TQ]

Saw the Sun recently! It still exists!

[@anniemack4282]

Showoff

[@russellcrosby8175]

Give me more, great stuff.

[@tomcuthbert7047]

Interesting video, as always. I’d be fascinated to know more about the ‘model’ that is often referred to, run by your computer system. Is it based on what has gone before…as in certain starting conditions in the past have led to certain outcomes in the forecast by way of historical precedent, or something else? Hope you are able to discuss some of what it does and how it does it!

[@KenMylne-f5z]

It is not based on what resulted from previous starting conditions, because every starting condition is unique, but it is tested on thousands of past cases. The model is a mathematical simulation of how the atmosphere works, using physics equations. We store information (pressure, temperature, humidity, etc) on a three-dimensional grid of points and the equations let us calculate how the atmosphere will evolve through time from the starting conditions. Basically the same model is also used for climate change projection as well. It is a truly massive computer code, extremely complex, and we are currently developing a massive reformulation to work on future generations of supercomputers. Definitely something we could do another Deep Dive on sometime.

[@tomcuthbert7047]

@ Great to hear from you - thanks for the response. In much of the met office video output, different computer models are often compared. Uncertainty in forecasting seems to arise where one model disagrees with another. My recollection from Physics is that the laws are always and everywhere true. Is the scope for divergence in the different models simply different starting conditions or the weight given to the application of different bits of physics or something else? I’d love to know more about these questions (to the extent that you may be able to discuss them) .

[@KenMylne-f5z]

​@@tomcuthbert7047the laws of physics are indeed precise (except on the sub-atomic scales of quantum mechanics!) However, our ability to represent all the physics in a computer is very limited...we would have to represent every molecule AND know what they are doing at the start precisely! (Even then the tiniest errors would grow due the chaos. ) so we have to make lots of approximations in how we simulate that physics. For small-scale processes the model has schemes to represent the average impact of lots of processes...turbulence, convection,cloud formation, friction with complex land surfaces etc). Different models use different approximations so get different results...and those differences can be amplified by chaos affecting larger scales

[@GrahamRead101]

That was so good and very interesting.

[@NorthamptonEcoFarm]

Great as always

[@KateHappiness-i1f]

Nice long deep dive, love the detail. Why is cold air dry?

[@KenMylne-f5z]

Thermodynamics…warm air is simply able to hold more moisture, so cold air becomes saturated more quickly. (Once saturated it cannot evaporate any more moisture, and if it cools more then moisture will condense out of it to form cloud or fog.) On the other side of the coin, warmer air holds more moisture and that is why we are seeing heavier rain events with climate warming.

[@elizabethmcpherson-lt9vh]

Agree - it has been so mild and dry - luxury - but dull and dangerous fog. Fed up reading in papers we are due a snow bomb - wont be in SE England Id love some snow